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Record W4210898578 · doi:10.12806/v21/i1/r10

CONCEPTUALIZING LEADERSHIP IN COMMUNITIES IN THE GLOBAL SOUTH EXPERIENCING GENERATIONAL POVERTY: An Exploratory Case Study in Muñoz, Dominican Republic

2022· article· en· W4210898578 on OpenAlexaff
Patricia Briscoe

Bibliographic record

VenueJournal of Leadership Education · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicTourism, Volunteerism, and Development
Canadian institutionsRegional Municipality of Niagara
Fundersnot available
KeywordsPovertyExploratory researchLeadership developmentPolitical scienceNarrativeWork (physics)Power (physics)Economic growthGlobal LeadershipGlobal SouthSociologyPublic relationsGeographySocial science

Abstract

fetched live from OpenAlex

This exploratory case study adds to the growing literature on leaders and leadership development in communities experiencing poverty in the global south. It explores how leadership is conceptualized among community-identified leaders in Muñoz, Dominican Republic. Drawn from semistructured interviews, the eight participant narratives provide insight into potential approaches for developing local leadership capacity that may help combat generational poverty. The recommendations from this study highlight the need to support the development of human capital using an anticolonial framework. The recommendations are especially relevant for leadership groups preparing to work or currently working in the nonprofit sector. By knowing how to better support the development of localized leadership within communities of poverty, external nonprofit agencies— particularly those from the global north—can better support communities and mitigate the risk of perpetuating colonial dynamics and power structures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.108
Threshold uncertainty score0.215

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0170.007
Scholarly communication0.0040.002
Open science0.0010.005
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.303
GPT teacher head0.382
Teacher spread0.079 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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